Correlations between copy number and mRNAseq expression
Adrenocortical Carcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Correlations between copy number and mRNAseq expression. Broad Institute of MIT and Harvard. doi:10.7908/C1377828
Overview
Introduction

A TCGA sample is profiled to detect the copy number variations and expressions of genes. This pipeline attempts to correlate copy number and Rnaseq data of genes across samples to determine if the copy number variations also result in differential expressions. This report contains the calculated correlation coefficients based on measurements of genomic copy number (log2) values and RNAseq expression of the corresponding feature across patients. High positive/low negative correlation coefficients indicate that genomic alterations result in differences in the expressions of mRNAseq the genomic regions transcribe.

Summary

The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are 968.9, 1936, 2623, 3230.6, 3835, 4419.4, 5021, 5644, 6352.1, respectively.

Results
Correlation results

Number of genes and samples used for the calculation are shown in Table 1. Figure 1 shows the distribution of calculated correlation coefficients and quantile-quantile plot of the calculated correlation coefficients against a normal distribution. Table 2 shows the top 20 features ordered by the value of correlation coefficients.

Table 1.  Counts of mRNAseq and number of samples in copy number and expression data sets and common to both

Category Copy number Expression Common
Sample 90 79 77
Genes 24776 17733 15230

Figure 1.  Summary figures. Left: histogram showing the distribution of the calculated correlations across samples for all Genes. Right: QQ plot of the calculated correlations across samples. The QQ plot is used to plot the quantiles of the calculated correlation coefficients against that derived from a normal distribution. Points deviating from the blue line indicate deviation from normality.

Table 2.  Get Full Table Top 20 features (defined by the feature column) ranked by correlation coefficients

Locus ID Gene Symbol Cytoband cor p-value q-value
1452 CSNK1A1 5q32 0.8455 0 0
79648 MCPH1 8p23.1 0.8257 0 0
80262 C16orf70 16q22.1 0.8242 0 0
84186 ZCCHC7 9p13.2 0.8089 0 0
6629 SNRPB2 20p12.1 0.8064 0 0
23039 XPO7 8p21.3 0.8008 0 0
29883 CNOT7 8p22 0.7941 0 0
10523 CHERP 19p13.11 0.7915 0 0
51125 GOLGA7 8p11.21 0.7898 0 0
4848 CNOT2 12q15 0.788 0 0
55585 UBE2Q1 1q21.3 0.7876 0 0
56890 MDM1 12q15 0.7823 0 0
51340 CRNKL1 20p11.23 0.7813 0 0
56888 KCMF1 2p11.2 0.7789 0 0
2339 FNTA 8p11.21 0.7784 0 0
58525 WIZ 19p13.12 0.7775 0 0
7265 TTC1 5q33.3 0.7773 0 0
79072 FASTKD3 5p15.31 0.7767 0 0
25912 C1orf43 1q21.3 0.7734 2.22044604925031e-16 3.37774253011958e-12
10296 MAEA 4p16.3 0.7732 2.22044604925031e-16 3.37774253011958e-12
Methods & Data
Input

Gene level (TCGA Level III) mRNAseq expression data and copy number data of corresponding gene derived by GISTIC pipelinePearson correlation coefficients were calculated for each pair of genes shared by the two data sets across all the samples that were common. The input file "ACC-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt " is generated in the pipeline mRNAseq_Preprocess in the stddata run.

Correlation across sample

Pairwise correlations between the log2 copy numbers and expressions of each gene across samples were calculated using Pearson correlation.

Download Results

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.